Spatio-temporal classification in point patterns under the presence of clutter

作     者：Siino, Marianna Rodriguez-Cortes, Francisco J. Mateu, Jorge Adelfio, Giada 

作者机构：Ctr Nazl Terremoti Ist Nazl Geofis & Vulcanol Rome Italy Univ Nacl Colombia Escuela Estadist Medellin Colombia Univ Jaume 1 Dept Matemat Castellon de La Plana Spain Univ Palermo Dipartimento Sci Econ Aziendali & Stat I-90128 Palermo Italy 

出 版 物：《ENVIRONMETRICS》 (环境计量学)

年 卷 期：2020年第31卷第2期

页      面：e2599-e2599页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 

基　　金：Italian Ministry of Education University and Research (MIUR) Universidad Nacional de Colombia, Hermes projects 

主　　题：clutter earthquakes EM algorithm features mixtures nearest-neighbor distances spatio-temporal point patterns 

摘      要：We consider the problem of detection of features in the presence of clutter for spatio-temporal point patterns. In previous studies, related to the spatial context, Kth nearest-neighbor distances to classify points between clutter and features. In particular, a mixture of distributions whose parameters were estimated using an expectation-maximization algorithm. This paper extends this methodology to the spatio-temporal context by considering the properties of the spatio-temporal Kth nearest-neighbor distances. For this purpose, we make use of a couple of spatio-temporal distances, which are based on the Euclidean and the maximum norms. We show close forms for the probability distributions of such Kth nearest-neighbor distances and present an intensive simulation study together with an application to earthquakes.